Evidence map›Paper›PMID 42478558›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2026

Array of Cointegrated Transistor-Based Artificial Neurons and Synapses for Neuromorphic Computing.

Sang-Won Lee, Seokho Seo, Hakcheon Jeong, Joon-Kyu Han, Yujin Kim, Dongeun Yoo, Joon-Ha Son, Ji-Man Yu, Shinhyun Choi, Yang-Kyu Choi

Abstract read
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sang-Won LeeSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Seokho SeoSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Hakcheon JeongSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Joon-Kyu HanDepartment of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.ORCID 0000-0002-8736-9091
Yujin KimSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Dongeun YooNational Nanofab Center (NNFC), Daejeon, Republic of Korea.
Joon-Ha SonSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Ji-Man YuSchool of Electronic Engineering, Kyungpook National University, Daegu, Republic of Korea.
Shinhyun ChoiSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID 0000-0002-5852-3360
Yang-Kyu ChoiSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID 0000-0001-5480-7027

Funding

IC Design Education CenterNational Research Foundation of Korea 2022M3F3A2A01072851National Research Foundation of Korea RS-2023-00217888National Research Foundation of Korea RS-2023-00260637National Research Foundation of Korea RS-2024-00333710National Research Foundation of Korea RS-2025-04162969
6 · The paper itself

Abstract

Neuromorphic computing seeks to replicate the computational efficiency and parallelism of the human brain by emulating its neural architecture. In this work, we present the Array of Cointegrated Transistor-Based Artificial Neurons and Synapses (ACTANS), a simplified hardware architecture that unifies transistors as both artificial neurons and synapses within a fully compatible complementary metal-oxide-semiconductor (CMOS) fabrication process. The artificial neurons and synapses are homotypic transistors that are structurally identical but functionally distinct. The proposed ACTANS consists of one neuron and sixteen connected synapses. In contrast to circuit-based neuromorphic systems that are limited by excessive area requirements and high-power consumption, and to non-CMOS systems that struggle to integrate neurons, synapses, and peripheral circuits owing to incompatibility with CMOS processes, the ACTANS architecture provides a compact device footprint and enables seamless neuron-synapse-circuit cointegration. The system is capable of performing cognitive tasks such as letter and pattern recognition.

Indexed as

Neural Networks, ComputerNeuronsSynapsesTransistors, ElectronicHumansSemiconductorsSoft ComputingCMOScointegrationneuromorphicneuronSONOSspiking neural network (SNN)synapse

Identifiers

PMID42478558
PMCPMC13549006

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.